摘要
在先进高速光纤通信系统中,密集波分复用技术的引入使得信号频谱间隔越来越窄,传统的带外光信噪比(OSNR)监测技术不再准确,需要进一步研究低成本的带内OSNR监测方案。文章提出了一种基于深度神经网络(DNN)的直调直检(IMDD)系统链路OSNR监测方案,采用550 000组数据集训练的5层DNN结构,在5~15 dB范围内,成功估计出了2 GBaud开关键控(OOK)信号的OSNR,平均绝对误差(MAE)小于0.8 dB。文章所提方案有望作为一种高效低成本方案,助力光网络智能运维。
In advanced high-speed fiber optic communication systems, due to the introduction of dense wavelength division multiplexing technology, the signal spectral interval is getting narrower and narrower, and the traditional out-of-band Optical Signal-to-Noise Ratio(OSNR) monitoring technology is no longer accurate. Therefore, further study is required in the low-cost in-band OSNR monitoring scheme. A Deep Neural Network(DNN) link OSNR monitoring scheme for Intensity-Modulation and Direct Detection(IMDD) system is proposed. We used a 5-layer DNN trained from 550 000 datasets to successfully estimate the OSNR of the 2 GBaud On-Off Key(OOK) signal in the range of 5 to 15 dB, and the Mean Absolute Error(MAE) is less than 0.8 dB.
作者
刘军
李伯中
陈芳
李子凡
郭莹
孙雨潇
邓春雪
张儒依
王英旭
LIU Jun;LI Bo-zhong;CHENG Fang;LI Zi-fan;GUO Ying;SUN Yu-xiao;DENG Cun-xue;ZHANG Ru-yi;WANG Ying-xu(State Grid Information and Telecommunication Branch,Beijing 100761,China)
出处
《光通信研究》
2023年第1期42-46,共5页
Study on Optical Communications
基金
国家重点研发计划资助项目(2021YFB2401000)。
